Intelligence gathering activities require the interception of signals from RF communication systems for reconnaissance and surveillance purposes. These activities include items such as detection of RF signals, the identification of sources transmitting those signals and determination of the position of each of those transmitting sources. However, a communication system which transmits direct sequence spread spectrum signals presents difficulties for both the detection of those signals, particularly for low-level signals, and in attempting to locate the positions of their transmitters.
Various types of direction finding apparatus exist at present. One direction finding apparatus uses a rotatable, highly directional, antenna connected to a receiver that can be tuned to a particular frequency. After the receiver is tuned to one frequency source, the antenna is rotated to provide a peak output from the receiver when the antenna is directed to the transmitting source for that particular frequency. This technique is time consuming and cannot perform any direction finding capability when the signal source is hopping in frequency.
Another direction finding technique is the use of two separate antenna spaced a known distance d apart from each other and measuring the time a signal from a transmitter arrives at each of the antenna. The direction of the transmitter, i.e. angle-of-arrival of the signal, can then be determined from the difference in time a signal arrives at the two antenna by cross-correlation of separate channels for each antenna. This process will provide the time difference between the signal's arrival at one antenna and its time of arrival at the other antenna. The angle-of-arrival of the signal with respect to the baseline between the antenna can then be determined from that time difference and the spacing d. This technique will operate satisfactorily for RF signals with a relatively narrow bandwidth. However, cross-correlation of wideband signals is a complex and very computationally expensive "brute-force" approach which is not practical for low-level BPSK or QPSK modulated spread spectrum signals.
Direct sequence spread spectrum systems spread their output power over bandwidths that are much greater than actually required for a given information data rate. This spreading is usually achieved by BPSK or QPSK modulation of the transmitted output signal with a high clock (chip) rate spreading sequence so as to pseudorandomly change the phase of the carrier signal at a very high rate, i.e. one that is much higher than the information data rate. The result will be the same as if the spreading sequence was added directly to the information data stream before it modulates the carrier. The bandwidth of the spreading sequence will, therefore, determine the bandwidth of the signal rather than the data rate.
The total power transmitted by direct sequence spread spectrum systems is unaffected by increasing the bandwidth of the output signal. This results in that increasing the spreading of the bandwidth of the transmitted signal will have the effect of reducing the signal's power spectral density. By spreading the bandwidth of the transmitted signal sufficiently, its power spectral density can even be reduced below the thermal background noise floor. A receiver intended to receive that transmitted signal will despread the received signal by removing the known spreading modulation to recover the initial narrow bandwidth data signal. Just as spreading the bandwidth of the transmitted signal reduced the signal's power spectral density, despreading at the intended receiver will increase the received signal's power spectral density so that the intended receiver will have a suitable signal-to-noise ratio (SNR) for demodulation of the data signal. Other receivers which do not know the particular spreading sequence used by the transmitter will be unable to despread the transmitted signal. Those other receivers will, as a result, have great difficulty in detecting and processing direct sequence spread spectrum signals. Consequently, direct sequence spread spectrum signals provide a covert means of communicating information.
Although direct sequence spread spectrum signals generally provide a covert communication system between a transmitter and an intended receiver, it is desirable for intelligence gathering purposes to be able to detect and locate those type of signal sources. A number of articles have been published in the area of spread Spectrum signal detection. One such article entitled "Optimal Detection of Digitally Modulated Signals" by Norman F. Krasner was published in the IEEE Transactions On Communications, Vol. COM-30, No. 5 on pages 885 to 895 in May 1982. This article describes optimal detectors and approximations of the optimal detectors for spread-spectrum signals which test for a signal present condition when the signal is buried in background white Gaussian noise. Another article by William A. Gardner entitled "Signal Interception: A Unifying Theoretical Framework for Feature Detection" was published on pages 897 to 906 of the IEEE Transactions On Communications, Vol. 36, No. 8, August 1988. This latter article discusses the relationships between a variety of previously proposed detectors using energy detecting techniques and proposed detectors using schemes that exploit the modulation characteristics of the signals to be detected and which is referred to as spectral correlation detection. A still further article on "Presence Detection of Binary-Phase-Shift-Keyed and Direct-Sequence Spread-Spectrum Signals Using a Prefilter-Delay-and-Multiply Device" by John F. Kuehls et al was published on pages 915 to 933 of the IEEE Journal on Selected Areas in Communications, Vol. 8, No. 5 in June 1990. This further article considers the problem of detecting the presence of either binary-phase-shift-keyed (BPSK) signals or BPSK direct sequence spread spectrum (DS/SS) signals in Gaussian noise. This article mentions that BPSK signals are not periodic because of the random nature of the sequence which shifts their phase and, hence, have a continuous Fourier spectra which makes them difficult to detect using a conventional analog spectrum analyzer or Fast Fourier Transforms. That article mentions, however, that it is known that discrete spectral components will arise when certain nonlinear operations are applied to BPSK signals and that these components are often detectable using spectrum analysis or FFT techniques. In fact, practically any nonlinear operation applied to BPSK and QPSK signals will generate these components with varying degrees of success. Therefore, a nonlinear operation can serve for the detection of BPSK signal presence by providing discrete spectral components from an unknown BPSK continuous-spectrum signal. That article then discusses a particular nonlinear operation using a quadratic transformation known as prefilter-delay-and-multiply (PFDM) for the detection of BPSK signals.